Time-Sensitive Networking (TSN) ensures reliable traffic delivery in industrial automation, multimedia, and automotive systems. While effective in wired networks, wireless TSN (WTSN) faces challenges like delays and interference, complicating traffic scheduling. This paper presents a data-driven approach to improve WTSN management by addressing the residual service time (RST) problem, which increases link latency. Tested in a Wi-Fi TSN-based environment, the proposed WTSN digital twin framework preserves TSN traffic guarantees while significantly reducing RST and hence link latency.

The densification of Wi-Fi deployments means that fully distributed random channel access is no longer sufficient for high and predictable performance. Therefore, the upcoming IEEE 802.11bn amendment introduces multi-access point coordination (MAPC) methods. This paper addresses a variant of MAPC called coordinated spatial reuse (C-SR), where devices transmit simultaneously on the same channel, with the power adjusted to minimize interference. The C-SR scheduling problem is selecting which devices transmit concurrently and with what settings. We provide a theoretical upper bound model, optimized for either throughput or fairness, which finds the best possible transmission schedule using mixed-integer linear programming. Then, a practical, probing-based approach is proposed which uses multi-armed bandits (MABs), a type of reinforcement learning, to solve the C-SR scheduling problem. We validate both classical (flat) MAB and hierarchical MAB (H-MAB) schemes with simulations and in a testbed. Using H-MABs for C-SR improves aggregate throughput over legacy IEEE 802.11 (on average by 80% in random scenarios), without reducing the number of transmission opportunities per station. Finally, our framework is lightweight and ready for implementation in Wi-Fi devices.

Time-Sensitive Networking (TSN) plays a crucial role in ensuring determinism and low latency, vital for the demands of industrial applications. Integrating the benefits of wire-less networks, including mobility, presents a significant challenge in such environments. In this study, we propose a novel solution to address this challenge by introducing handover capabilities into wireless Time-Sensitive Networking (W-TSN). Through real-world development and testing, we present an optimized approach for minimizing handover delay and leveraging machine learning to select the optimal handover time and space moment in a two-dimensional environment, with low effect on time-sensitive traffic. Our findings demonstrate that our mechanism reduces handover delay below 10 milliseconds and optimizes the handover moment selection, leading to improvements in critical network parameters such as bandwidth and jitter.

Recent technologies of Wi-Fi are being widely in-corporated in smart factories with an expectation of real-time, flexible, reliable, and quality services. The current Wi-Fi offers a range of physical data rates based on channel quality but is limited to certain applications. With the traditional application and transport layer protocols being designed for wired networks, using them in bottleneck situations of industrial wireless networks poses certain drawbacks and one such drawback is the through-put degradation due to airtime unfairness. Using innovations like in-band network telemetry, application-network interaction, and the programmability of the kernel and intermediate devices, a reactive airtime feedback-based congestion control algorithm, RACC, for wireless networks is introduced in this paper. The designed algorithm reactively adapts the application data transfer rate based on the feedback from the access point and was implemented on commercial off-the-shelf devices. Using this algorithm, the throughput was improved 72% and the airtime unfairness was reduced to as low as 15% as compared to the CUBIC. The designed congestion control algorithm addresses the issue of airtime unfairness and throughput degradation in industrial wireless networks based on real-time network state.

With ever-increasing throughput-hungry applications running over WiFi, such as Virtual and eXtended Reality (VR/XR), on the one hand and the need for deterministic communication on the other, network densification is not an option. With dense network deployment interference between overlapping basic service set (OBSS) become the main source of system throughput drop and packet delays, decreasing the benefits of dense network. With the latest WiFi 7 standard being standardized, access point (AP) coordination is one of the key features foreseen to be added. With increased interactions between APs from different OBSS, spatial reuse feature can benefit in determining accurately the levels of interference and modulation and coding scheme (MCS) index to be used for concurrent transmissions. In this paper we show a centralized Coordinated Spatial Reuse (C-SR) algorithm implemented in the network controller that determines the transmit powers of the concurrent AP transmitters based on calculated interference levels in the main receiver. In addition, the algorithm determines the MCS index for each concurrent transmission. In a test-bed measurement setup, we show that the overall system goodput is increased by 20% and 33%, respectively, for the network topology where receivers are positioned in the inner zone between APs. In addition, the communication latency is maintained below certain threshold, compared to cases where C-SR is not activated.

As network management operations increasingly rely on automation and finer control actions, there is a need for precise telemetry systems. In-band Network Telemetry (INT) methods use data packets to carry telemetry and give real-time insights about network performance. Existing solutions often require specialized hardware or offer limited runtime configuration options. This work presents an INT Framework for heterogeneous private networks, targeting industrial and multimedia applications. The framework is designed to be flexible and runtime-reconfigurable, addressing challenges in real-world applications. We provide implementation details of our elements supporting the configurability and the consolidation of raw telemetry into high-level Quality of Service (QoS) metrics. We evaluated the framework in a testbed with wired and wireless devices. The results show the accuracy in monitoring QoS, as well as an analysis of synchronization requirements, showcasing the feasibility of our framework for solutions requiring precise and flexible QoS monitoring.

As industries increasingly rely on advanced networking solutions, Time-Sensitive Networking (TSN) has emerged as an essential tool, ensuring smooth and reliable communication in mission-critical applications. However, while TSN does a lot for industrial systems, there is still a whole world of not-utilized potential in wireless communication. To extend wired TSN with wireless capabilities, imec’s openwifi platform has been extended with TSN features. To speed up the implementation of new Wi-Fi features in the openwifi platform, as well as to test their feasibility in larger-scale network scenarios we implemented the key TSN features of openwifi in the ns-3 simulator. In this paper, we evaluate how the selection of transmission opportunity (TXOP) duration affects network performance in shared time slots, as well as the impact of different shifts between shared time slots. The ns-3 implementation is validated against openwifi as well.

Time-sensitive networking (TSN) is proposed to support deterministic communication for industrial automation use cases. To harvest the wireless communication flexibility, TSN features have been extended to the wireless domain as well. One of the key TSN features is the ability to assign transmission schedules to different traffic flows in the network with the aim of reducing time slot access delay on each network node. In the wireless domain, this becomes even more challenging due to the shared medium, lower reliability, and slower transmission rates compared to wired systems, reducing the available time resources. In this paper we look at utilizing genetic algorithms to support scheduling of traffic flows from different wireless end devices in a shared schedule. Two optimization functions are defined. The first optimization is based on minimizing the overall shared air time between different end nodes, while the second optimization is based on maximizing time slots that can be used without any interference. Both optimizations aim to reduce the collision probability. With these initial results, we identify the best parameters for genetic algorithms and examine the initial population's impact on overall performance. We show that a fully randomized initial population does not achieve the highest fitness value, even after several generations.

Real-time applications are employed in today's pri-vate professional networks to support process handling and improve the efficiency of production. For supporting such applications, communication networks need to support deterministic communication with bounded low latency and high reliability. Time-sensitive networking (TSN) is used for such purposes, recently extended to wireless networks as well. To further improve the network catering to such real-time applications, it is crucial for end devices to expose their requirements to the network. On top of that, new wireless features like OFDMA, implemented in IEEE 802.11ax (Wi-Fi 6), can improve wireless time-sensitive networks (W-TSNs) by improving communication efficiency. This paper looks at reducing the overhead of OFDMA and integrating UL-OFDMA with wireless TSN to support time-sensitive flows. We show that when both features are integrated, it reduces the latency by ~ 16 times compared to Wi-Fi with UL-OFDMA scenario while giving 50 % better air time utilization compared to the wireless TSN scenario.

End-to-end low-latency deterministic communication, next to high-reliability communication, is one of the key features that communication systems are expected to provide for industrial systems. To achieve time-sensitive networking (TSN), a set of standards have already been designed and deployed for wired industrial communication systems, coexisting or replacing other long-living technologies such as Fieldbus, Profibus, or Modbus. Wireless time-sensitive networking (W-TSN) is getting traction with the development of the newest WiFi generation (IEEE 802.11be) as well as advances in cellular networking. One of the challenges in W-TSN is scheduling and isolation of time-critical traffic in the shared wireless medium. In this paper we present a solution, called dynamic traffic classification, to give faster dedicated access to the wireless medium for packets of highly-time-sensitive flows, that can be generated randomly. Dynamic traffic classification utilizes so-called shadow queues implemented in FPGA-based WiFi baseband SDR platform, openwifi, to prioritize channel access of certain packets over others. We show that the channel access latency in the case of dynamic traffic classification does not depend on the scheduling cycle, but on the distribution of dedicated time slots inside the schedule cycle. As such we achieve to decrease the end-to-end latency by 75% in case of longer communication cycles with wider space between communication time slots.

The emergence of Time-Sensitive Networking (TSN) has enabled network determinism to a new level, offering high reliability and bounded latency for critical communications. However, the unpredictable nature of traffic generation also poses new challenges to TSN. While TSN is designed to maintain backward compatibility with the 802.1 standards, many end nodes may not be equipped to understand TSN. This can result in a less deterministic TSN, and suboptimal resource utilization, mainly driven by Residual Service Time (RST). To address these challenges, this study proposes three scheduling mechanisms to reduce RST: q-learning, active time slot update, and polynomial forecasting. Real-world data captured from our wireless-TSN (W-TSN) evaluation kit is used to compare the proposed approaches in terms of one-way latency. The results show that the machine learning approach outperforms the other methods in terms of overall latency. However, it is less effective in identifying the optimal time slot position compared to the other methods.

Deterministic performance and reliable operation are vital for many applications with industrial-grade requirements. Such applications rely on Time-Sensitive Networking (TSN) to enable time-critical deterministic communication. While standardization efforts were focused mainly on TSN features for wired domains, recent advances in wireless technologies (e.g., Wi-Fi 6/7) are extending time-sensitive communication towards wireless networks as well. However, achieving multi-domain LAN/ Wireless LAN (WLAN) end-to-end TSN communication requires addressing challenges on end-to-end time synchronization, multi-domain control plane interoperability, run-time end-to-end scheduling, and fine-grained monitoring. Because state-of-the-art TSN controllers’ scope lays far below these new required capabilities, in this work we present a novel, fully-programmable controller for end-to-end TSN-enabled networks. Our controller is based on a modular architecture to be adaptable to challenges arising when shifting the standard TSN scope towards WLAN domain. We deploy a proof-of-concept in a cloud-wired environment to evaluate its key performance indicators when handling increasing numbers of nodes and simultaneous requests. Further, we run experiments on real TSN-enabled networks comprising Ethernet and Wi-Fi technologies, demonstrating the effectiveness of the controller in performing seamless fine-grained traffic control in both domains.

Industrial communication systems provide deterministic and reliable communication between various industrial components. In the past several decades, different communication technologies (Fieldbus, Real-Time Ethernet (RTE)) were used to achieve such determinism. Recently, Time-Sensitive Networking (TSN) is being utilized in industrial environments to support end-to-end low latency deterministic communication by providing mechanisms for accurate time synchronization, traffic scheduling/shaping, and reliability. With many use cases requiring portability and seamless mobility, such features are being developed for wireless networks as well, expanding the time-sensitive communication to the wireless domain. Wireless TSN’s aim is to provide wired TSN-like features, achieving wired-wireless interoperability and flattening the automation system pyramid. In this paper, we present an integration between the wireless TSN and PROFINET. We show that the safety-related applications can be supported seamlessly, providing deterministic communication and reliability under best-effort traffic load in the wireless network. The solution is evaluated in terms of the achieved end-to-end latency and the probability of failure per hour of the fail-safe communication. It is shown that by using wireless time-sensitive networking with dedicated time slots per traffic flow a safety integrity level up to grade 4 can be achieved.

Time-sensitive networking (TSN) is widely used in industrial environments to support low-latency deterministic communications. Innovation to bring time-sensitive networking to wireless networks is getting traction. Besides enabling real-time and deterministic communications, Wireless Time-Sensitive Networks (W- TSN) should provide flexibility and easy deploy-ment, key characteristic requirements for industrial networks. Nevertheless, current research in this field focuses on adapting wired TSN features to the wireless world, namely accurate time synchronization and traffic scheduling, essential processes for wireless end devices such as automated and impact-less association procedure are not considered until now. This work proposes a W - TSN impactless association procedure that provides time synchronization and traffic scheduling for prospect W - TSN clients during the association phase by utilization of beacons. As such, prospect clients can perform association procedure in a controlled fashion avoiding collisions with other, already-associated, W - TSN clients. The presented procedure is designed, implemented, and tested in a real-world scenario on top of a wireless Software Defined Radio (SDR) platform with the IEEE802.11 standard. The results show high accuracy synchro-nization on client frame transmissions even with challenging scheduling timeslots of 128 μs.

Precision time protocol (PTP), a state-of-the-art clock synchronization protocol primarily designed for wired networks, has recently gained attention in the wireless community, due to the increased use of the IEEE 802.11 wireless local area networks (WLAN) in real-time distributed systems. However, all the existing WLAN-based PTP designs either incorporate software timestamping (TS) delivering poor clock synchronization accuracy, or hardware (HW) TS providing better synchronization accuracy at the cost of a significant amount of HW overhead. Moreover, the performance of the existing PTP solutions is mostly evaluated in single-hop wireless networks, while the performance across wired and wireless networks is taken for granted. In this article, a new software-defined-radio-based approach to implement PTP is introduced and validated for the IEEE 802.11 WLAN. Instead of using a dedicated HW clock, the solution utilizes the timing synchronization function clock, an existing clock in the IEEE802.11 standard for synchronization between access point and WLAN stations. The performance of the proposed solution is first investigated within a single-hop WLAN and then across wired–wireless networks. Experimental results unveil that 90% of the absolute clock synchronization error falls within 1.4$\mu \mathrm{s}$.

Many applications use Transmission Control Protocol (TCP) to achieve end-to-end reliable, ordered, and error-free data transfer in the network. The decisions are entirely based on the partial end-to-end information obtained from the acknowledgment packets. With several applications moving towards the wireless domain or wired-wireless domain, there has been advancements in the field of application-network interaction and innovations to obtain real-time network monitoring information on a per-hop basis. This paves a way for extensibility and customization of transport protocols. In this paper, we use detailed real-time in-band network telemetry information to adjust the data transfer at the sender side by modifying the congestion control algorithms in real time. This new technique is tested for different network scenarios and the obtained results indicate that a more network-aware TCP design can greatly increase performance under lossy conditions. The implemented technique illustrates how tighter interactions between higherlayer protocols and the network, in combination with real-time telemetry, can facilitate the way for novel, more adaptive protocol designs.

In-band network telemetry (INT) monitoring is getting traction in the recent years for its ability to offer high-granularity network information on per-hop, per-flow and end-to-end basis. Such detailed network monitoring helps in better network management and accurate network (re)configuration, supporting automated network management and control. However, until now the collected INT information is used as is, without any classification based on its provided information value. In this paper we derive the Age of Information (AoI) mathematical model to calculate the INT hop-time average AoI and the impact of reporting on the INT AoI. Such metric can be used to reduce the network overhead in term of INT reporting by not sending old AoI INT and determining the information accuracy. We also show that the INT hop-time average AoI for a layer three INT implementation for a wireless network depends heavily on the communication latency between each hop and end hop, and that it is bounded by the end-to-end communication latency averaged over the number of hops.

While the Internet of Things continues to grow, the LoRaWAN standard is generating special interest due to its open-source nature, ultralow-power consumption and long-range connectivity. Recent works have explored the challenges of implementing LoRaWAN, with scalability being considered one of the major bottlenecks imposed by its Aloha-based medium access control (MAC) layer. Despite much on-going research on LoRaWAN scheduling aimed at alleviating this concern, experimental approaches are rarely found in the literature. In this work, we describe the steps taken and the technical issues overcome to move from a low-overhead synchronization and scheduling concept to its real-world implementation on top of LoRaWAN Class A. Accordingly, an end-to-end architecture was designed and deployed on top of STM32L0 MCUs, which communicate with a central entity responsible for providing synchronization metrics and allocating transmission slots on demand. The clock drift of devices was measured in a temperature-controlled chamber, which served as a basis to define slot lengths in the network. As a result, an operational end-to-end system was implemented and evaluated for different setup scenarios, with 10-ms accuracy being achieved. Our experimental results show significant improvements in packet delivery ratios with respect to Aloha-based setups, especially under high network loads (up to 29% for SF12), thereby demonstrating the feasibility of the presented approach.

Most industrial applications demand determinism in terms of latency, reliability, and throughput. This goes hand in hand with the increased complexity of real-time network programability possibilities. To ensure network performance low-overhead, high-granularity, and timely network verification techniques need to be deployed. The first cornerstone of network verification ability is to enable end-to-end network monitoring, including end devices too. To achieve this, this article shows a novel and low overhead in-band network telemetry and monitoring technique for wireless networks focusing on IEEE 802.11 networks. A design of in-band network telemetry enabled node architecture is proposed and its proof of concept implementation is realized. The PoC realization is used to monitor a real-life SDN-based wireless network, enabling on-the-fly (re)configuration capabilities based on monitoring data. In addition, the proposed monitoring technique is validated in terms of monitoring accuracy, monitoring overhead, and network (re)configuration accuracy. It is shown that the proposed in-band monitoring technique has 6 times lower overhead than other active monitoring techniques on a single-hop link. Besides this, it is demonstrated that (re)configuration decisions taken based on monitored data fulfill targeted application requirements, validating the suitability of the proposed monitoring technique.

The fifth generation of mobile networks (5G) and the Software- Defined Radio Access Networks (SD- RAN) architecture envision to support lower latency, enhanced reliability, massive connectivity, and improved energy efficiency. In this context, low latency is considered crucial and Ultra-Reliable Low Latency Communication (URLLC) as one of the key enablers. Currently, IEEE 802.11 networks cannot be programmed fine-grained enough nor manage multiple networks at runtime. Besides, in such scenarios, the coarse-grained level of monitoring information has been hindering troubleshooting and management. In this paper, we present an SDN-based framework where fine-grained End-to-End (E2E) network statistics can be gathered using Inband Network Telemetry (INT) and used for network control and management. With such fine-grained network information, we show how our system can enhance the Quality of Service (QoS) delivery through slice orchestration in IEEE 802.11 Radio Access Networks (RANs).

Wireless netWorks are becoming more complex while applications on top are becoming more demanding. To maintain network performance in terms of latency, throughput and reliability, continuous verification of the performance, possibly followed by on-the-fly network (re)configuration is needed. To achieve this, the way wireless network monitoring is being done needs to be reconsidered and should evolve towards more timely, low overhead and fine-grained monitoring. This paper shows hoiv in-band network telemetry (INT) monitoring can achieve these objectives. An INT-enabled node architecture is designed as well as novel INT options. By means of an implementation on WiFi Linux devices, the concept is validated by tracking the behavior of a real network.

This paper presents a Convolutional Neural Network (CNN) approach for classification of low power wide area network (LPWAN) technologies such as Sigfox, LoRA and IEEE 802.15.4g. Since the technologies operate in unlicensed sub-GHz bands, their transmissions can interfere with each other and significantly degrade their performance. This situation further intensifies when the network density increases which will be the case of future LPWANs. In this regard, it becomes essential to classify coexisting technologies so that the impact of interference can be minimized by making optimal spectrum decisions. State-of-the-art technology classification approaches use signal processing approaches for solving the task. However, such techniques are not scalable and require domain-expertise knowledge for developing new rules for each new technology. On the contrary, we present a CNN approach for classification which requires limited domain-expertise knowledge, and it can be scalable to any number of wireless technologies. We present and compare two CNN based classifiers named CNN based on in-phase and quadrature (IQ) and CNN based on Fast Fourier Transform (FFT). The results illustrate that CNN based on IQ achieves classification accuracy close to 97% similar to CNN based on FFT and thus, avoiding the need for performing FFT.

Recently, LoRaWAN has attracted much attention for the realization of many Internet of Things applications because it offers low-power, long-distance, and low-cost wireless communication. Recent works have shown that the LoRaWAN specification for class A devices comes with scalability limitations due to the ALOHA-like nature of the MAC layer. In this paper, we propose a synchronization and scheduling mechanism for LoRaWAN networks consisting of class A devices. The mechanism runs on top of the LoRaWAN MAC layer. A central network synchronization and scheduling entity will schedule uplink and downlink transmissions. In order to reduce the synchronization packet length, all time slots that are being assigned to an end node are encoded in a probabilistic space-efficient data structure. An end node will check if a time slot is part of the received data structure in order to determine when to transmit. Time slots are assigned based on the traffic needs of the end nodes. We show that in case of a nonsaturated multichannel LoRaWAN network with synchronization being done in a separate channel, the packet delivery ratio (PDR) is easily 7% (for SF7) to 30% (for SF12) higher than in an unsynchronized LoRaWAN network. For saturated networks, the differences in PDR become more profound as nodes are only scheduled as long as they can be accommodated given the remaining capacity of the network. The synchronization process will use less than 3-mAh extra battery capacity per end node during a one year period, for synchronization periods longer than three days. This is less than the battery capacity used to transmit packets that are going to be lost in an unsynchronized network due to collisions.

We develop and benchmark four RSS localisation algorithms where different a priori knowledge is required. The selection of the best algorithm depends on the availability of additional information on path loss exponent and/or transmit power. We compare our algorithms with centroid localization and show that the algorithms provide better results for shadowing on the values not exceeding 6dB. We perform experiments and simulations with Bluetooth Low Energy and LoRaWAN technologies and select the best technology and algorithm for localisation in large open industrial environments.

Modern connected devices are equipped with the ability to connect to the Internet using a variety of different wireless network technologies. Current network management solutions fail to provide a fine-grained, coordinated, and transparent answer to this heterogeneity, while the lower layers of the OSI stack simply ignore it by providing full separation of layers. To address this, we propose the ORCHESTRA framework to manage the different devices in heterogeneous wireless networks and introduce capabilities such as packet-level dynamic and intelligent handovers (both interand intra-technology), load balancing, replication, and scheduling. The framework is the first of its kind in providing a fine-grained packet-level control across different technologies by introducing a fully transparent virtual medium access control layer and an software-defined networking-like controller with global intelligence. Furthermore, we present a novel optimization problem formulation that can be solved to optimally configure the network. We provide a thorough evaluation through simulations and a prototype implementation. We show that our framework enables, in a real-life setting, transparent and realtime inter-technology handovers and that coordinated load balancing can double the network-wide throughput across different scenarios.

Local area networks (LANs) are employed by a plethora of heterogeneous consumer devices, equipped with the ability to connect to the Internet using a variety of different wireless network technologies. Existing solutions and the lower layers of the OSI stack are unfit to cope with this heterogeneity. For instance, dynamical inter-technology switching is user-of application-based. We propose the ORCHESTRA framework to manage the different devices in heterogeneous wireless local area networks (WLANs) and introduce capabilities such as packet-level dynamic and intelligent handovers (both inter- and intratechnology), load balancing, replication, and scheduling. The framework consists of a controller that is capable of communicating with both existing Software-Defined Networking (SDN) and Network Function Virtualization (NFV) controllers and with devices containing a newly introduced virtual Medium Access Control (MAC) layer. We show that the virtual MAC enables transparent and real-time inter-technology handovers and that our solution scales up to two thousands of clients.

LoRa is a long range, low power, low bit rate, single hop wireless communication technology. It is intended to be used for Internet of Things (IoT) networks, where devices are battery powered and limited bandwidth is needed. In combination with its scalability and the low end device price, LoRa is a candidate technology for low bandwidth industrial applications with a high number of communication devices spread across large areas. The use case for this paper is taken from the flower industry, where a large number of trolleys need to communicate with a server during their movement across the auction floor area. Once trolleys are outside of the auction floor they can use the public LoRaWAN network to communicate with the server, without switching communication technology. The LoRaWAN network consists of multiple end nodes and a single gateway per cell, acting as a transparent bridge between the end nodes and the network server. The measurements show that with a single LoRa gateway we can cover an indoor area of around 34000m2 only with spreading factor 7, while for spreading factor 12 the total covered area will be even higher. Also, the area outside the factory is covered when switching to spreading factor 12. We also show that the number of nodes (trolleys) that can be served by a gateway in such a case can be as high as 6000.

Due to the fast emergence of location-based services and the absence of a widely adopted localization technology for indoor environments, Indoor Localization Systems have become a central topic of research in the last decade. Although there is a significant amount of research targeting indoor localization technologies and their performance, most of these efforts only focus on theory, system design or evaluation in non-industrial environments, usually offices or healthcare spaces. In this work, a detailed performance evaluation of two commercially available accurate localization technologies, based on Bluetooth Low Energy (LE) and Ultra-wideband (UWB), in an industrial environment is presented to create an experimental understanding of their behaviour in similar conditions and to investigate their potential to be used in industrial applications with concrete localization requirements. For this purpose, these localization technologies are examined with respect to various performance criteria in several scenarios in a real industrial site.

As LoRaWAN networks are actively being deployed in the field, it is important to comprehend the limitations of this low power wide area network technology. Previous work has raised questions in terms of the scalability and capacity of LoRaWAN networks as the number of end devices grows to hundreds or thousands per gateway. Some works have modeled LoRaWAN networks as pure ALOHA networks, which fails to capture important characteristics such as the capture effect and the effects of interference. Other works provide a more comprehensive model by relying on empirical and stochastic techniques. This paper uses a different approach where a LoRa error model is constructed from extensive complex baseband bit error rate simulations and used as an interference model. The error model is combined with the LoRaWAN MAC protocol in an ns-3 module that enables to study multichannel, multispreading factor, multi-gateway, bi-directional LoRaWAN networks with thousands of end devices. Using the LoRaWAN ns-3 module, a scalability analysis of LoRaWAN shows the detrimental impact downstream traffic has on the delivery ratio of confirmed upstream traffic. The analysis shows that increasing gateway density can ameliorate but not eliminate this effect, as stringent duty cycle requirements for gateways continue to limit downstream opportunities.

Wireless communication is an enabling technology for industrial automation. For mobile industrial devices operating in large areas, the performance of the wireless handover process is crucial. For the welfare of industrial processes short time communication outage must be ensured, especially for time-critical traffic. This paper assesses the handover performance for three industrial real-life use cases with different requirements. It covers handover performance under heavy interference, its impact on time-critical traffic and on broadcast traffic latency, followed by lessons learned and opportunities for further research.